Title
Automated classification of cells in sub-epithelial connective tissue of oral sub-mucous fibrosis-An SVM based approach
Abstract
Quantitative evaluation of histopathological features is not only vital for precise characterization of any precancerous condition but also crucial in developing automated computer aided diagnostic system. In this study segmentation and classification of sub-epithelial connective tissue (SECT) cells except endothelial cells in oral mucosa of normal and OSF conditions has been reported. Segmentation has been carried out using multi-level thresholding and subsequently the cell population has been classified using support vector machine (SVM) based classifier. Moreover, the geometric features used here have been observed to be statistically significant, which enhance the statistical learning potential and classification accuracy of the classifier. Automated classification of SECT cells characterizes this precancerous condition very precisely in a quantitative manner and unveils the opportunity to understand OSF related changes in cell population having definite geometric properties. The paper presents an automated classification method for understanding the deviation of normal structural profile of oral mucosa during precancerous changes.
Year
DOI
Venue
2009
10.1016/j.compbiomed.2009.09.004
Comp. in Bio. and Med.
Keywords
DocType
Volume
Sub-epithelial connective tissue (SECT),Oral sub-mucous fibrosis (OSF),Multi-level thresholding,Support vector machine (SVM)
Journal
39
Issue
ISSN
Citations 
12
0010-4825
4
PageRank 
References 
Authors
0.43
7
7